Numerical analysis of axial compressive behavior of RC short columns subjected to non-uniform fire: A meso-scale study

The bearing capacity and durability of reinforced concrete (RC) structures can be affected by fire. In this study, a three-dimensional (3D) meso-scale simulation model for RC short column subjected to axial compression after exposure to fire was established. The degradation effect of mechanical properties of steel bars and concrete materials after high temperature was taken into account. The bond-slip behavior between longitudinal steel bars and concrete was also considered in the model. Based on the present simulation method, the failure mode and failure mechanism of the RC short columns were investigated. Moreover, the effects of fire scenario and fire duration on the axial compression performance of RC short columns were further investigated. It is found that the meso-scale numerical model can effectively simulate the mechanical behavior of RC short columns under axial load. Moreover, with the increase of fired surfaces and fire duration, the peak bearing capacity, axial compression stiffness and ductility decrease. The mechanical properties of short columns decrease more quickly under non-uniform fire. By comparing the theoretical value with the numerical simulation value of Nut/Nu, it is found that the theoretical value is conservative

Pollution characteristics, long-term variation trend, and health risk assessment of lead in ambient PM2.5 in Jinan

BackgroundA number of studies have shown that heavy metals in atmospheric PM2.5 have impacts on human health, while studies on the impact of long-term and low-concentration exposure to lead in PM2.5 on human health are limited. ObjectiveTo investigate the pollution characteristics of lead in ambient PM2.5 and assess its chronic health risks. MethodsDaily PM2.5 concentration data in Jinan from 2014 to 2019 were collected, and the year-by-year trend of PM2.5 concentration was analyzed. Licheng District (an industrial area) and Shizhong District (a residential area) were elected to install an ambient PM2.5 monitoring stationrespectively. The sampling instrument was a 100 L·min−1 high-flow PM2.5 sampler, with a cumulative sampling time of 20-24 h per day, using a quartz fiber filter membrane for lead detection and a glass fiber filter membrane for PM2.5 determination. The sampling frequency was 7 consecutive days per month from the 10th to the 16th (A total of 493 d were sampled and some were missing; 172 d during the heating period and 321 d during the non-heating period). Two PM2.5 samples were collected in one monitoring site each day. A total of 986 samples were collected in one monitoring site. The lead content in PM2.5 samples was detected by inductively coupled plasma mass spectrometry. The concentration of PM2.5 was measured by weighing method. The annual average concentration and enrichment factor of lead in PM2.5, the change trend of lead content per unit mass of PM2.5, and the difference between heating period and non-heating period from 2014 to 2019 were estimated. Technical guide for environment health risk assessment of chemical exposure (WS/T 777-2021) was used to assess the health risks of exposure to lead in PM2.5. ResultsThe average annual concentration of lead in PM2.5 ranged from 23.2 ng·m−3 to 154.7 ng·m−3. The average concentration in heating period from 2015 to 2019 was higher than that in non-heating period, and the differences in 2015, 2017, and 2019 were statistically significant (P < 0.01 or 0.001). The enrichment factors ranged from 200 to 1342 in 2014 to 2019. The average enrichment factors in heating period in 2015, 2017, and 2018 was higher than those in non-heating period, and the difference was statistically significant (P < 0.05 or 0.001). The lead contents per unit mass of PM2.5 ranged from 493 ng·mg−1 to 1944 ng·mg−1, and the differences between heating period and non-heating period in 2014, 2017, and 2018 were statistically significant (P < 0.05 or 0.001). The average annual concentration and enrichment factor of lead in PM2.5 showed a downward trend, and thus the lead content per unit mass of PM2.5 also decreased. From 2014 to 2019, the carcinogenic risk of lead in PM2.5 in Jinan ranged from 1.69×10−8 to 2.45×10−6, showing a significant downward trend year by year, and the 95th percentile decreased by 3%-46% from the previous year. The carcinogenic risk level of lead was reduced to an acceptable level (<1×10−6) after 2017. ConclusionFrom 2015 to 2019, lead concentration and enrichment factor in PM2.5 increase during heating period compared with non-heating period, but it is not completely consistent of lead content in PM2.5 per unit mass. From 2014 to 2016, exposure to lead in PM2.5 may elevate carcinogenic risk to human. After 2017, the carcinogenic risks of exposure to lead in PM2.5 are at an acceptable level

Boosting moisture induced electricity generation from graphene oxide through engineering oxygen-based functional groups

Harvesting energy from ubiquitous moisture is attracting growing interest for directly powering electronic devices. However, it is still challenging to fabricate high-performing moisture-electric generators (MEGs) with high and stable electric output. Herein, we report a simple strategy to modify the oxygen-based groups of graphene oxide using hydrochloric acid treatment, which boosts the electric output based on the device structure of graphene oxide/polyvinyl alcohol (GO/PVA) MEGs. The resulting MEG enables a stable voltage of 0.85 V and a current of 9.28 µA (92.8 µA·cm-2), which are among the highest values reported so far. More excitingly, electric output gets further improved by simply assembling four MEG units in series or parallel. Moreover, the MEG shows great commercial potential for flexible and wearable applications. Driven by these advancements, the assembled MEGs can successfully power sensors and calculators. This work opens a new era of advance for a new energy conversion technology able to directly powering electronic devices.C.C. acknowledges support from the Spanish Ministry of Science, Innovation and Universities under the "Ramon y Cajal" fellowship RYC2018-024947-IPeer ReviewedPostprint (published version

Study on the Evaluation Scheme of Emergency Response Capacity of The Three Gorges - Gezhouba Dam

according to different navigation condition and environment of traffic emergency strategy, using fuzzy algorithm to the actual situation of ship parameters of the actual situation assessment, the result will be according to the instruction from the data graph for the actual operation, effectively avoid risk. Ships that should be properly arranged in a non-emergency session should avoid the concentration of traffic in heavy traffic and cause unnecessary security risks. The general function of ship safety is established by mathematical modeling, and the application function is used to control the ship. Ensure safe navigation